Search Results for author: Sha Li

Found 26 papers, 17 papers with code

Enhancing Knowledge Selection for Grounded Dialogues via Document Semantic Graphs

no code implementations NAACL 2022 Sha Li, Mahdi Namazifar, Di Jin, Mohit Bansal, Heng Ji, Yang Liu, Dilek Hakkani-Tur

In this work, we propose to automatically convert the background knowledge documents into document semantic graphs and then perform knowledge selection over such graphs.

Multi-Task Learning Response Generation +1

EVEDIT: Event-based Knowledge Editing with Deductive Editing Boundaries

no code implementations17 Feb 2024 Jiateng Liu, Pengfei Yu, Yuji Zhang, Sha Li, Zixuan Zhang, Heng Ji

The dynamic nature of real-world information necessitates efficient knowledge editing (KE) in large language models (LLMs) for knowledge updating.

knowledge editing

If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents

no code implementations1 Jan 2024 Ke Yang, Jiateng Liu, John Wu, Chaoqi Yang, Yi R. Fung, Sha Li, Zixuan Huang, Xu Cao, Xingyao Wang, Yiquan Wang, Heng Ji, ChengXiang Zhai

The prominent large language models (LLMs) of today differ from past language models not only in size, but also in the fact that they are trained on a combination of natural language and formal language (code).

Code Generation

RESIN-EDITOR: A Schema-guided Hierarchical Event Graph Visualizer and Editor

1 code implementation5 Dec 2023 Khanh Duy Nguyen, Zixuan Zhang, Reece Suchocki, Sha Li, Martha Palmer, Susan Brown, Jiawei Han, Heng Ji

In this paper, we present RESIN-EDITOR, an interactive event graph visualizer and editor designed for analyzing complex events.

Defining a New NLP Playground

no code implementations31 Oct 2023 Sha Li, Chi Han, Pengfei Yu, Carl Edwards, Manling Li, Xingyao Wang, Yi R. Fung, Charles Yu, Joel R. Tetreault, Eduard H. Hovy, Heng Ji

The recent explosion of performance of large language models (LLMs) has changed the field of Natural Language Processing (NLP) more abruptly and seismically than any other shift in the field's 80-year history.

Instruct and Extract: Instruction Tuning for On-Demand Information Extraction

1 code implementation24 Oct 2023 Yizhu Jiao, Ming Zhong, Sha Li, Ruining Zhao, Siru Ouyang, Heng Ji, Jiawei Han

However, when it comes to information extraction - a classic task in natural language processing - most task-specific systems cannot align well with long-tail ad hoc extraction use cases for non-expert users.

Instruction Following

OpenPI-C: A Better Benchmark and Stronger Baseline for Open-Vocabulary State Tracking

1 code implementation1 Jun 2023 Xueqing Wu, Sha Li, Heng Ji

Open-vocabulary state tracking is a more practical version of state tracking that aims to track state changes of entities throughout a process without restricting the state space and entity space.

Non-Sequential Graph Script Induction via Multimedia Grounding

1 code implementation27 May 2023 Yu Zhou, Sha Li, Manling Li, Xudong Lin, Shih-Fu Chang, Mohit Bansal, Heng Ji

To automate the induction of such graph scripts for given tasks, we propose to take advantage of loosely aligned videos of people performing the tasks.

GLEN: General-Purpose Event Detection for Thousands of Types

1 code implementation16 Mar 2023 Qiusi Zhan, Sha Li, Kathryn Conger, Martha Palmer, Heng Ji, Jiawei Han

Finally, we perform error analysis and show that label noise is still the largest challenge for improving performance for this new dataset.

Event Detection Event Extraction

Open Relation and Event Type Discovery with Type Abstraction

1 code implementation30 Nov 2022 Sha Li, Heng Ji, Jiawei Han

To tackle this problem, we introduce the idea of type abstraction, where the model is prompted to generalize and name the type.

Event Extraction Relation +2

Open-Vocabulary Argument Role Prediction for Event Extraction

1 code implementation3 Nov 2022 Yizhu Jiao, Sha Li, Yiqing Xie, Ming Zhong, Heng Ji, Jiawei Han

Specifically, we formulate the role prediction problem as an in-filling task and construct prompts for a pre-trained language model to generate candidate roles.

Event Extraction Language Modelling

Code4Struct: Code Generation for Few-Shot Event Structure Prediction

1 code implementation23 Oct 2022 Xingyao Wang, Sha Li, Heng Ji

As a case study, we formulate Event Argument Extraction (EAE) as converting text into event-argument structures that can be represented as a class object using code.

Code Generation Event Argument Extraction +3

Dynamic Global Memory for Document-level Argument Extraction

1 code implementation ACL 2022 Xinya Du, Sha Li, Heng Ji

Extracting informative arguments of events from news articles is a challenging problem in information extraction, which requires a global contextual understanding of each document.

Event Argument Extraction Sentence

Enhanced Knowledge Selection for Grounded Dialogues via Document Semantic Graphs

no code implementations15 Jun 2022 Sha Li, Mahdi Namazifar, Di Jin, Mohit Bansal, Heng Ji, Yang Liu, Dilek Hakkani-Tur

Providing conversation models with background knowledge has been shown to make open-domain dialogues more informative and engaging.

Multi-Task Learning Response Generation +1

Schema-Guided Event Graph Completion

no code implementations6 Jun 2022 Hongwei Wang, Zixuan Zhang, Sha Li, Jiawei Han, Yizhou Sun, Hanghang Tong, Joseph P. Olive, Heng Ji

Existing link prediction or graph completion methods have difficulty dealing with event graphs because they are usually designed for a single large graph such as a social network or a knowledge graph, rather than multiple small dynamic event graphs.

Link Prediction

Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion

1 code implementation Findings (ACL) 2022 Yiqing Xie, Jiaming Shen, Sha Li, Yuning Mao, Jiawei Han

Typical DocRE methods blindly take the full document as input, while a subset of the sentences in the document, noted as the evidence, are often sufficient for humans to predict the relation of an entity pair.

Document-level Relation Extraction Relation

The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Prediction

1 code implementation EMNLP 2021 Manling Li, Sha Li, Zhenhailong Wang, Lifu Huang, Kyunghyun Cho, Heng Ji, Jiawei Han, Clare Voss

We introduce a new concept of Temporal Complex Event Schema: a graph-based schema representation that encompasses events, arguments, temporal connections and argument relations.

Document-Level Event Argument Extraction by Conditional Generation

1 code implementation NAACL 2021 Sha Li, Heng Ji, Jiawei Han

On the task of argument extraction, we achieve an absolute gain of 7. 6% F1 and 5. 7% F1 over the next best model on the RAMS and WikiEvents datasets respectively.

Document-level Event Extraction Event Argument Extraction +2

Relation Learning on Social Networks with Multi-Modal Graph Edge Variational Autoencoders

no code implementations4 Nov 2019 Carl Yang, Jieyu Zhang, Haonan Wang, Sha Li, Myungwan Kim, Matt Walker, Yiou Xiao, Jiawei Han

While node semantics have been extensively explored in social networks, little research attention has been paid to profile edge semantics, i. e., social relations.


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